A space mapping method and system for teleoperated robots based on taught stiffness

Abstract

The application belongs to the technical field of teleoperation robots, and discloses a space mapping method and system for a teleoperation robot based on teaching stiffness. The method comprises the following steps: S1, constructing a relationship formula of the stiffness and position of the slave robot end in the teaching stage by dividing the working stage of the teleoperation robot into the teaching stage and the actual operation stage; S2, dividing the working space of the slave robot end into a fast motion space, a fine operation space and a transition space, and constructing a relationship formula of the expected position and attitude of the slave robot end in the actual operation stage; S3, obtaining mapping coefficients of the position and attitude of each space based on the teaching stiffness characteristics; and S4, solving the expected position and attitude of the slave robot end in each space in the actual operation stage, so as to realize the space mapping of the teleoperation robot. According to the application, the motion in the actual operation stage is smooth and compliant, and the motion stage switching does not need to rely on a button. The method is simple, flexible, functional, low in calculation cost and practical.

Description

Technical Field

[0001] This invention belongs to the technical field of teleoperated robots, and more specifically, relates to a spatial mapping method and system for teleoperated robots based on teaching stiffness. Background Technology

[0002] Teleoperation technology is an interdisciplinary field that combines robotics, control engineering, and computer science. It can isolate operators from dangerous environments and make decisions that combine the experience and wisdom of human operators with the stability and accuracy of robots. Therefore, it is widely used in fields such as outer space, medicine, nuclear environment, and deep-sea exploration.

[0003] In teleoperated flaw detection, the slave robot's motion must be capable of both large-scale rapid movement and small-scale fine manipulation, while also exhibiting smooth and compliant motion. Most existing workspace mapping methods are designed based on parameters such as the position and velocity of the master and slave robots, resulting in complex spatial mapping algorithms, jitter during mode switching, poor universality and practicality, or reliance on external buttons for mode switching, leading to poor intelligence. Furthermore, these methods require the operator to learn and adapt to the spatial mapping method without incorporating the operator's compliance skills. Therefore, in practice, considerable training is often necessary to achieve satisfactory teleoperation results.

[0004] Therefore, a mapping method for teleoperated robots is needed to solve the above problems. Summary of the Invention

[0005] In view of the above-mentioned defects or improvement needs of the prior art, the present invention provides a spatial mapping method and system for teleoperated robots based on teaching stiffness, which solves the technical problem that the operator's compliance skills are not incorporated into the spatial mapping method in the prior art.

[0006] To achieve the above objectives, according to one aspect of the present invention, a spatial mapping method for a teleoperated robot based on teach stiffness is provided, the method comprising the following steps:

[0007] S1 divides the working phase of the teleoperated robot into a teaching phase and a practical phase. During the teaching phase, it collects the position, velocity, acceleration and external forces of the end effector of the slave robot at different times. It then calculates the stiffness of the end effector of the slave robot at different times and uses the collected position and calculated stiffness at different times to construct the relationship between the stiffness and position of the end effector of the slave robot during the teaching phase.

[0008] S2 divides the workspace of the end-effector robot into a rapid motion space, a fine operation space, and a transition space, and constructs a relational formula between the expected position and posture of the end-effector robot in the practical stage. This relational formula includes the position mapping coefficient and posture mapping coefficient of the end-effector robot in each space.

[0009] S3, taking into account the characteristic that the stiffness values ​​remain basically unchanged in the rapid motion space and the fine operation space, determines the range of values ​​for the position mapping sparsity and attitude mapping coefficients of the rapid motion space and the fine operation space and assigns them according to their respective ranges. At the same time, it assigns values ​​to the attitude mapping coefficients of the transition space. Using the position correspondence and stiffness of the slave robot in the teaching stage and the practical operation stage, it constructs the relationship of the position mapping coefficients of the transition space in the practical operation stage and solves it accordingly.

[0010] S4 uses the position mapping coefficients and attitude mapping coefficients of each space to solve the relationship between the expected position and attitude of the end effector of the robot in the practical stage, thereby obtaining the expected position and attitude of the end effector of the robot in each space in the practical stage, thus realizing the spatial mapping of the teleoperated robot.

[0011] More preferably, in step S1, the stiffness at different times is calculated according to the following formula:

[0012]

[0013] Where λ is the tuning parameter, X t It is the position error auxiliary vector, Y t I is an auxiliary vector, and I is the identity matrix.

[0014] More preferably, in step S1, the relationship between the stiffness and position of the end effector of the slave robot during the teaching phase is expressed according to the following formula:

[0015]

[0016] Where c1, c2, c3, and c4 are the coefficients of the sigmoid function, obtained by fitting using the least squares method; x is the position of the end effector of the robot during the teaching process.

[0017] More preferably, in step S2, the relationship between the desired position and orientation of the end effector of the slave robot during the practical operation phase is as follows:

[0018] X sd =X s0 +k(X m -X m0 )

[0019] RPY sd =RPYs0 +k RPY (RPY m -RPY mo )

[0020] Among them, X sd X is the desired position of the end effector of the slave robot. s0 X is the initial end-effector position of the slave robot in its current spatial location; m X represents the end effector position as indicated by the master robot. mo It corresponds to X s0 The end effector position of the master robot, k is the position mapping coefficient, RPY sd It is the desired pose of the end-user robot, RPY s0 This is the initial posture of the slave robot in its current spatial environment, RPY m It is the posture of the main robot, RPY m0 It corresponds to RPY s0 The posture of the master robot, k RPY These are attitude mapping coefficients.

[0021] More preferably, in step S3, the value ranges of the position mapping coefficients and attitude mapping coefficients of the rapid motion space and the fine operation space are as follows:

[0022] and

[0023] and

[0024] in, k is the position mapping coefficient of the slave robot in the rapid motion space. smax It is the maximum position mapping coefficient in the fast motion space, which is determined by the workspace of the master and slave robots. These are the attitude mapping coefficients of the end-user robot in a fast-moving space. It is the position mapping coefficient of the end-user robot in the fine operation space; It is the attitude mapping coefficient of the slave robot in the fine operation space.

[0025] More preferably, in step S3, the pose mapping coefficients of the transition space are assigned values ​​in the following manner: These are the pose mapping coefficients in the transition space.

[0026] More preferably, in step S31, the correspondence between the end-effector position of the slave robot in the transition space during the practical operation phase and the end-effector position of the slave robot in the teaching phase is as follows:

[0027]

[0028] Among them, X s X1 represents the position of the slave robot in the transition space; X2 represents the minimum and maximum positions of the slave robot in the transition space, respectively; X1 and X2 represent the minimum and maximum positions of the transition phase during the teaching process, respectively.

[0029] More preferably, the relationship between the position mapping coefficients of the transition space in the practical stage is as follows:

[0030]

[0031] in, k is the position mapping coefficient of the slave robot in the transition space. x,max k x,min These are the maximum and minimum stiffness values ​​during the transition phase of the teaching process. These are the position mapping coefficients of the end-effector robot in the rapid motion space and the fine manipulation space, respectively. g(·) is the position and stiffness function fitted during the teaching phase, and f(X) is the position mapping coefficient of the end-effector robot in the rapid motion space and the fine manipulation space, respectively. s ) is a mapping function from the position of the end robot to the position in the teaching stage during the practical operation.

[0032] According to another aspect of the present invention, a spatial mapping system for a teleoperated robot based on teach stiffness is provided, comprising a processor for executing the spatial mapping method for a teleoperated robot based on teach stiffness as described above.

[0033] According to another aspect of the present invention, a computer-readable storage medium is provided having a computer program stored thereon, which, when executed by a processor, implements the spatial mapping method for a teleoperated robot based on teach stiffness as described above.

[0034] In summary, the technical solutions conceived by this invention have the following beneficial effects compared with the prior art:

[0035] 1. This invention establishes the connection between the practical operation stage and the teaching stage based on the stiffness of the teaching stage. The stiffness value can better characterize the operator's compliant operation skills, ensuring the stability and compliance of the spatial mapping method in practical applications.

[0036] 2. This invention obtains the relationship between stiffness and position through the state information of the robot teaching process and fits it with the sigmoid function, transferring stiffness-based compliant operation skills to the master-slave heterogeneous teleoperation space mapping method;

[0037] 3. Why were these coefficients chosen in this way in this invention? and and A fixed position mapping coefficient satisfies the characteristic of relatively constant stiffness during the teaching phase, aligns with the operator's compliant operating skills, and, when selected within a certain range, can meet the task requirements of different operators under different working conditions. During rapid movement and transition phases, the posture remains largely unchanged, and a proportional posture mapping coefficient satisfies the operator's operating habits. However, during the fine-tuning phase, a smaller posture mapping coefficient can meet the operator's needs for precise operation.

[0038] 4. This invention divides the workspace of the slave robot and proposes a position and attitude mapping coefficient design method based on teaching stiffness, in addition to the proposed position incremental mapping and attitude RPY angle incremental mapping methods. This enables scaling of position and attitude, meeting the needs of large-scale rapid movement and small-scale fine operation, with smooth transitions. The method is simple, practical, and universally applicable to master-slave heterogeneous teleoperation systems.

[0039] 5. The multi-mode spatial mapping method designed in this invention updates the selected mode in real time by judging the position of the slave robot in each control cycle of the robot. Therefore, it does not require the intervention of external signals such as buttons and has a high degree of intelligence. Attached Figure Description

[0040] Figure 1 This is a flowchart of a spatial mapping method for a teleoperated robot based on teaching stiffness, constructed according to a preferred embodiment of the present invention.

[0041] Figure 2 This is a schematic diagram of a master-slave robot in a remotely operated ultrasonic flaw detection system constructed according to a preferred embodiment of the present invention, wherein (a) is a force feedback device and (b) is a collaborative robot;

[0042] Figure 3 This is a schematic diagram of the workspace partitioning of the slave robot constructed according to a preferred embodiment of the present invention;

[0043] Figure 4 This is a schematic diagram of the stiffness of the teaching stage constructed according to a preferred embodiment of the present invention;

[0044] Figure 5 This is a transition space position mapping coefficient diagram of the slave robot constructed according to a preferred embodiment of the present invention;

[0045] Figure 6 This is a schematic diagram of the end-effector trajectory of the master-slave robot constructed according to a preferred embodiment of the present invention;

[0046] Figure 7This is a schematic diagram of the master-slave robot RPY angle constructed according to a preferred embodiment of the present invention, wherein (a) is a schematic diagram of the robot's posture rotating around the z-axis at an angle α, (b) is a schematic diagram of the robot's posture rotating around the y-axis at an angle β, and (c) is a schematic diagram of the robot's posture rotating around the x-axis at an angle γ. Detailed Implementation

[0047] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention. Furthermore, the technical features involved in the various embodiments of this invention described below can be combined with each other as long as they do not conflict with each other.

[0048] like Figure 1 As shown, a spatial mapping method for a teleoperated robot based on teach stiffness is proposed, which includes the following steps:

[0049] S1 Teaching Phase: The operator drags the slave robot to move, completing rapid motion, fine motion, and transitional motion, and collects the robot's position x during the teaching process. t ,speed acceleration and the environmental force f experienced by the robot end effector e,t The stiffness value during the teaching process is calculated using the following steps. For example... Figure 2 The diagram shows the master-slave robot structure of a remotely operated ultrasonic flaw detection system.

[0050]

[0051]

[0052] Where, x t,d It is the expected position at time t during the teaching process; It is the position error at time t during the teaching process; y t is an auxiliary variable; b is the damping value. Defining the time sliding window length as L, then:

[0053]

[0054] Y t =[y t-L ,y t-L+1 ,…,y t+L ]

[0055] In one embodiment of the present invention, b = 20 is chosen. The time sliding window length L = 3 is defined.

[0056] The stiffness value at time t can then be calculated using the following formula:

[0057]

[0058] Wherein, λ is the tuning parameter, and in one embodiment of the present invention, λ = 0.005.

[0059] S2 establishes a forward kinematics model based on the geometric parameters of the master and slave robots to obtain the size and shape of their respective workspaces. For the slave robot, its workspace W is divided, and a sphere with a center point P and a radius r is selected according to the actual task scenario. min The sphere is used as the fine operation space W2; with point P as the center point of the sphere and an inner diameter of r. min The outer diameter is r max The hollow sphere serves as the transition space W3; the remaining portion below the workspace W serves as the rapid movement space W1. In one embodiment of the invention, the spaces are constructed according to Table 1 below:

[0060] Table 1. Workspace range of master and slave robots (unit: meters)

[0061] <![CDATA[P mimax ]]> <![CDATA[P mimin ]]> <![CDATA[P simax ]]> <![CDATA[P simin ]]> X direction 0.93 0.2 0.8 -0.8 Y direction 0.615 -0.667 0.8 -0.8 Z direction 0.86 -0.5 1.15 -0.25

[0062] Furthermore, for the slave robot, its workspace W is divided as follows: Figure 3 As shown, the center point of the sphere is selected as P = [0.65 0.16 0.25] based on the task scenario. T The radius is r min A sphere with a diameter of 0.15m is used as the fine operation space W2; with point P as the center of the sphere, the inner diameter is r. min The outer diameter is r max A hollow sphere with a diameter of 0.2m serves as the transition space W3; the remaining portion below the working space W serves as the rapid movement space W1.

[0063] The master-slave heterogeneous space mapping method used in this invention is: position incremental mapping method and attitude RPY angle incremental mapping method.

[0064] X sd =X s0 +k(X m -X m0 )

[0065] Among them, X sd X represents the desired position of the end effector of the slave robot. s0 This indicates the initial end-effector position of the slave robot in its current spatial location; X m X represents the end effector position represented by the master robot. mo This indicates that it corresponds to X s0 The position of the end effector of the master robot, k represents the position mapping coefficient.

[0066] RPY sd =RPY s0 +k RPY (RPY m -RPY mo )

[0067] RPY sd RPY represents the desired pose of the end-user robot. s0 RPY represents the initial posture of the end-user robot in its current spatial location. m Indicates the posture of the master robot, RPY m0 It corresponds to RPY s0 The posture of the master robot, k RPY This is represented as the attitude mapping coefficient.

[0068] S3 establishes a workspace mapping method for a master-slave heterogeneous teleoperated robot in a rapid motion space: Based on the characteristic that the stiffness value remains basically unchanged during rapid motion in the teaching phase, fixed position and attitude mapping coefficients are adopted. The specific coefficients are selected by the operator's operating habits and satisfy the following: and In one embodiment of the present invention, and

[0069] A method for mapping the workspace of a master-slave heterogeneous teleoperated robot in a fine manipulation space is established: Based on the characteristic that the stiffness value remains basically unchanged during the teaching phase and fine manipulation, fixed position and attitude mapping coefficients are adopted. The specific coefficients are selected by the operator's operating habits and satisfy the following conditions: and In one embodiment of the present invention, and

[0070] A method for mapping the workspace of a master-slave heterogeneous teleoperated robot with the slave robot in the transition space is established: a fixed attitude mapping coefficient is used. Meanwhile, to ensure a smooth transition between modes, the stiffness changes during the teaching process are used to design the position mapping coefficients.

[0071]

[0072] Through the function f(X) s Mapping the position of the end-user robot to the robot's equivalent position x′ during the teaching phase:

[0073]

[0074] X sX1 represents the position of the slave robot in the transition space; X2 represents the minimum and maximum positions of the slave robot in the transition space, respectively; X1 and X2 represent the minimum and maximum positions of the slave robot during the transition phase of the teaching process, respectively.

[0075] Based on the characteristics of stiffness changes during the teaching phase, the sigmoid function is used to fit the relationship g(x) between position and stiffness during the teaching process using the least squares method:

[0076]

[0077] Where c1, c2, c3, and c4 are the coefficients of the sigmoid function, obtained by fitting using the least squares method; x represents the robot's position during the teaching process.

[0078] The relationship between position and stiffness during the teaching process is mapped to the position mapping coefficient of the slave robot in the transition space using the following formula.

[0079]

[0080] Where, k x,max k x,min These are the maximum and minimum stiffness values ​​during the transition phase of the teaching process.

[0081] In one embodiment of the present invention,

[0082]

[0083]

[0084]

[0085] S4 uses the position mapping coefficients and attitude mapping coefficients of each space to solve the relationship between the expected position and attitude of the end effector of the robot in the practical stage, and obtains the expected position and attitude of the end effector of the robot in each space in the practical stage.

[0086] By embedding the above algorithm into the teleoperation control system, the position of the slave robot can be determined in each control cycle, thus enabling the automatic selection of the appropriate position and posture mapping mode.

[0087] Figure 4 This diagram illustrates the changes in positional stiffness during the teaching process. Vertical dotted lines divide the rapid motion region, fine motion region, and transition region. Dashed lines represent the calculated stiffness values, and solid lines represent the fitted stiffness values.

[0088] Figure 5This diagram illustrates the change in the transition space mapping coefficients, demonstrating how the position mapping coefficients can be smoothly and seamlessly adjusted based on the robot's location within the transition space. Transition to This ensures the smooth and stable movement of the slave robot.

[0089] Figure 6 The diagram shows the end-effector trajectories of the master and slave robots, where dashed lines represent the master robot's trajectory and solid lines represent the slave robot's trajectory. During the rapid movement phase, the small-range movements of the master robot correspond to the large-range movements of the slave robot; during the transition phase, the transition is smooth with no noticeable jitter; during the fine-operation phase, the large-range movements of the master robot correspond to the small-range movements of the slave robot. This invention achieves the functions of large-range movement, small-range fine-operation, and smooth transition, and transfers the operator's compliant operation skills, demonstrating good experimental results.

[0090] Figure 7 This diagram illustrates the RPY angle of the master and slave robots, where the dashed line represents the trajectory of the master robot and the solid line represents the trajectory of the slave robot. To the left of the vertical dashed line indicates the slave robot's ability to completely track the master robot's posture during the rapid movement and transition phases. To the right of the vertical dashed line indicates the fine manipulation phase, where changes in the master robot's posture correspond to smaller changes in the slave robot's posture. This demonstrates the posture mapping function of the present invention and exhibits good experimental results.

[0091] The purpose of this invention is to provide a master-slave heterogeneous teleoperation space mapping method for transferring operator compliant manipulation skills based on robot teaching stiffness. During the teaching phase, the robot performs rapid and fine movements, and the stiffness values ​​during the teaching process are calculated. The workspace of the slave robot is divided, and position and attitude mapping coefficients are designed based on incremental position mapping and incremental attitude RPY angle mapping. According to the operator's teaching stiffness and operating habits, fixed position and attitude mapping coefficients are adopted to ensure the achievement of rapid movement and fine manipulation task requirements. Simultaneously, to ensure smooth mode switching, the stiffness changes of the robot during the transition process in the teaching trajectory are collected, fitted using the sigmoid function, and the relationship between the position mapping coefficients and position in the transition space is derived using a linear mapping method. The mode transition is smooth and does not require the use of buttons for mode switching. This method is simple, flexible, highly functional, computationally inexpensive, and highly practical.

[0092] Those skilled in the art will readily understand that the above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A spatial mapping method for a teleoperated robot based on teach stiffness, characterized in that, The method includes the following steps: S1 divides the working phase of the teleoperated robot into a teaching phase and a practical phase. During the teaching phase, it collects the position, velocity, acceleration and external forces of the end effector of the slave robot at different times. It then calculates the stiffness of the end effector of the slave robot at different times and uses the collected position and calculated stiffness at different times to construct the relationship between the stiffness and position of the end effector of the slave robot during the teaching phase. S2 divides the workspace of the end-effector robot into a rapid motion space, a fine operation space, and a transition space, and constructs a relational formula between the expected position and posture of the end-effector robot in the practical stage. This relational formula includes the position mapping coefficient and posture mapping coefficient of the end-effector robot in each space. S3 determines the range of values ​​for the position mapping coefficient and attitude mapping coefficient in the rapid motion space and the fine operation space, based on the characteristic that the stiffness values ​​remain basically unchanged in the rapid motion space and the fine operation space, and assigns values ​​according to their respective ranges. At the same time, the attitude mapping coefficient of the transition space is assigned a value. Using the position correspondence and stiffness of the slave robot in the teaching stage and the practical operation stage, the relationship of the position mapping coefficient of the transition space in the practical operation stage is constructed and solved accordingly. S4 uses the position mapping coefficients and attitude mapping coefficients of each space to solve the relationship between the expected position and attitude of the end effector of the robot in the practical stage, thereby obtaining the expected position and attitude of the end effector of the robot in each space in the practical stage, thus realizing the spatial mapping of the teleoperated robot.

2. The spatial mapping method for a teleoperated robot based on teaching stiffness as described in claim 1, characterized in that, In step S1, the stiffness at different times is calculated according to the following formula: Where λ is the tuning parameter, X t It is the position error auxiliary vector, Y t I is an auxiliary vector, and I is the identity matrix.

3. The spatial mapping method for a teleoperated robot based on teaching stiffness as described in claim 2, characterized in that, In step S1, the relationship between the stiffness and position of the end effector of the slave robot during the teaching phase is expressed according to the following formula: Where c1, c2, c3, and c4 are the coefficients of the sigmoid function, obtained by fitting using the least squares method; x is the position of the end effector of the robot during the teaching process.

4. The spatial mapping method for a teleoperated robot based on teaching stiffness as described in claim 1, characterized in that, In step S2, the relationship between the desired position and orientation of the end effector of the robot during the practical phase is as follows: X sd =X s0 +k(X m -X m0 ) RPY sd =RPY s0 +k RPY (RPY m -RPY mo ) Among them, X sd X is the desired position of the end effector of the slave robot. s0 X is the initial end-effector position of the slave robot in its current spatial location; m X represents the end effector position as indicated by the master robot. mo It corresponds to X s0 The end effector position of the master robot, k is the position mapping coefficient, RPY sd It is the desired pose of the end-user robot, RPY s0 This is the initial posture of the slave robot in its current spatial environment, RPY m It is the posture of the main robot, RPY m0 It corresponds to RPY s0 The posture of the master robot, k RPY These are attitude mapping coefficients.

5. The spatial mapping method for a teleoperated robot based on teach stiffness as described in claim 4, characterized in that, In step S3, the value ranges of the position mapping coefficients and attitude mapping coefficients of the rapid motion space and the fine operation space are as follows: and and in, k is the position mapping coefficient of the slave robot in the rapid motion space. smax It is the maximum position mapping coefficient in the rapid motion space, determined by the workspace of the master and slave robots. These are the attitude mapping coefficients of the end-user robot in a fast-moving space. It is the position mapping coefficient of the slave robot in the fine operation space. It is the attitude mapping coefficient of the slave robot in the fine operation space.

6. A spatial mapping method for a teleoperated robot based on teach stiffness as described in claim 4 or 5, characterized in that, In step S3, the pose mapping coefficients of the transition space are assigned values ​​in the following manner: These are the pose mapping coefficients in the transition space.

7. A spatial mapping method for a teleoperated robot based on teach stiffness as described in claim 1 or 2, characterized in that, In step S31, the correspondence between the end-effector position of the slave robot in the transition space during the practical operation phase and the end-effector position of the slave robot in the teaching phase is as follows: Among them, X s X1 represents the position of the slave robot in the transition space; X2 represents the minimum and maximum positions of the slave robot in the transition space, respectively; X1 and X2 represent the minimum and maximum positions of the transition phase during the teaching process, respectively.

8. The spatial mapping method for a teleoperated robot based on teaching stiffness as described in claim 7, characterized in that, The relationship between the position mapping coefficients of the transition space in the practical stage is as follows: in, k is the position mapping coefficient of the slave robot in the transition space. x,max k x,min These are the maximum and minimum stiffness values ​​during the transition phase of the teaching process. These are the position mapping coefficients of the end-effector robot in the rapid motion space and the fine manipulation space, respectively. g(·) is the position and stiffness function fitted during the teaching phase, and f(X) is the position mapping coefficient of the end-effector robot in the rapid motion space and the fine manipulation space, respectively. s ) is a mapping function from the position of the end robot to the position in the teaching stage during the practical operation.

9. A spatial mapping system for a teleoperated robot based on teach-in stiffness, characterized in that, Includes a processor for executing the spatial mapping method for a teleoperated robot based on teach stiffness as described in any one of claims 1-8.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the spatial mapping method for a teleoperated robot based on teaching stiffness as described in any one of claims 1-8.

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